Using principles of just-in-time to improve new product development process.

The role of technology in traditional manufacturing has been mainly ineffective. Organizations often used pieces of new technologies, such as robots, as a quick way to solve manufacturing problems like bottleneck, long lead-time, or poor quality. Similarly, in sequential NPD, pieces of new technologies such as CAD have been applied to isolated parts of the process (Adler, 1989).

In a JIT manufacturing system, technology comes after simplification and understanding of the entire system, and technology is not viewed as a substitute, or shortcut to process improvement. Rather, technology has been utilized after process analysis and simplification has been performed.

The role of technology, especially information technology, in simultaneous NPD is enormous. Simultaneous engineering requires that the design team with diverse expertise makes a large number of interrelated decisions regarding the form, fit, function, cost, quality, and other aspects of the design (Karagozoglu and Brown, 1993). This requires supply and processing of relevant information from multiple sources in a coordinated manner. Effective use of technologies and tools can dramatically shorten NPD time, reduce the number of prototypes, cut costs, and improve quality of the design (Karagozoglu and Brown, 1993; Rosenthal, 1992).

MEASURES OF SUCCESSFUL NEW PRODUCT DEVELOPMENT

Comparison of the factors in Tables 1 and 2 shows a high degree of consistency between conventional manufacturing and sequential NPD. The Tables also demonstrate remarkable similarities between JIT manufacturing and NPD using simultaneous engineering. Since JIT focuses on eliminating waste, improving quality, reducing costs, shortening delivery time, and improving teamwork, it is natural to apply the same principles to NPD. From an investment point of view, successful product design ultimately results in products that can be manufactured and sold profitably. The following dimensions of quality, time, competency, and costs, directly related to profit, are often used to assess the performance of a product design (Ulrich and Eppinger, 2000; Wheelwright and Clark, 1992):

1. Quality: Does the product satisfy customer needs? Quality is ultimately reflected in the price customers are willing to pay, the market share, and the bottom line profit. Design quality probles are often the result of incomplete information and miscommunication among different functions. In NPD process, quality often means a minimal number of redesign or rework. In this paper, the number of design changes during the development process and the early manufacturing phase is used as an indicator of design quality.

2. Development time: How quickly is the organization able to complete the development process? Development time is the length of time between initial idea generation until new product is ready for introduction to the market. Shorter development time raises the competitive value of the new product in terms of premium price, larger market share, and higher profit margin. Product development time determines how responsive the firm can be to competition and to technology, as well as how quickly the organization receives financial returns from the sales of the product.

3. Developing Competency: Is the organization able to develop future products better, faster, and cheaper as a result of their experience with product development? Development competency is an asset that an organization can use to develop products more effectively and economically in the future. A competent workforce and effective use of technologies are important elements of organizational competency. Frequency of new product introduction to the market is used as a measure of development competency.

4. Development cost: How much did it cost to develop the product? This is the one-time total cost from the early idea generation until the product is ready for manufacturing. For most organizations, development cost is a significant portion of the budget and must be considered in light of budget realities and the timing of budget allocations.

5. Manufacturing cost: How much would it cost to produce the product? This cost includes initial investment on equipment and tools as well as the incremental cost of manufacturing the product. There is a close relationship between manufacturing cost and the type of decisions made during the early design stage (Huthwaite, B. 1991). For instance, early manufacturing involvement in NPD promotes design-for-manufacturing and design-for-assembly techniques, which can lead to fewer parts, easier assembly, less scrap, higher yields and ultimately lower manufacturing cost.

RESEARCH HYPOTHESES

Given the analysis of the factors in Tables 1 and 2, one would expect to see strong relationships between the deployment of JIT principles and NPD performances. This leads to the following hypotheses:

H1: Organizations with JIT manufacturing system will design new products with better quality.

H2: Organizations with JIT manufacturing system will design new products faster.

H3: Organizations with JIT manufacturing system will design new products with better development competency (i.e. more frequently).

H4: Organizations with J1T manufacturing system will design new products with less development cost.

H5: Organizations with JIT manufacturing system will design new products with less manufacturing cost.

RESEARCH METHODOLOGY AND RESULTS

Testing the above hypotheses required data collection on NPD performances for the organizations who have adopted JIT principles and reported data before and after their implementation. The method used in this research is the analysis of existing data primarily from two sources. The first source, published data from previous JIT and NPD research since early 1980's. In our search, we were interested in those publications that have reported not only the main benefits of JIT, but also reported their NPD performance before and after JIT implementation. The second source of the data was electronic search of various databases. The Lexis/Nexis database was used to identify the firms that have publicly announced their JIT implementation. The database was searched for keywords such as JIT production, lean production, zero inventory, and Kanban production. The search pattern was repeated for other databases such as the Wall Street Journal Index database, and Standard and Poor's COMPUSTAT annual industrial, and annual research databases. Overall, from the period of 1982 to 2000, 51 companies were found that have adopted JIT principles and reported their NPD performances before and after JIT implementation. Some well known U.S., Japanese, and European companies were among the companies in the list. The collected data covers organizations on different industries ranging from automotive, electronics, communication, computers, home appliances, pharmaceutical, chemical, tools, and household products. Out of a sample of 51 companies, 23 reported the number of design changes before and after JIT, 26 reported development time and development competency, and 22 companies reported development cost and manufacturing cost before and after JIT implementation. A summary of the statistical results is given in Table 3.

Table 3 provides useful information regarding the NPD performances before and after JIT implementation. In terms of design quality, the average number of design changes before JIT implementation is 4.46 while after JIT adoption is 2.77, an improvement of 61 percentage. Table 3 also shows average development time prior to JIT is 34.88 months while after JIT implementation is 22.92 months, an improvement of 52 percent. For development competency, the average time between introductions of new products is 57.40 months prior to JIT and it is 33.50 months after JIT adoption, an improvement of 71 percent. Table 3 also indicates that JIT organizations enjoy a 38 percent reduction in development cost and 33 percent reduction in manufacturing cost. Since data on NPD performances covers organizations before and after JIT implementation, tests of hypotheses with dependent samples were used to test the hypotheses. From Table 3, it is clear that all hypotheses are strongly supported by the data. Hypothesis H1 stated that organizations with JIT production system will design new products with better quality. This relationship is strongly supported by the data as indicated by the t-value of 4.16 and the P-value of less than 0.05 percent. The relationship between JIT and NPD time, hypothesis H2, is also strongly supported with the t-value of 4.97 and the P-value of less than 0.05 percent. The stated relationship between JIT and the frequency of new production introduction, hypothesis H3, is also strongly supported by the data with the t-value of 4.91 and the P-value of less than 0.05 percentage. Finally, JIT has a significant impact on reducing development cost, hypothesis H4, and manufacturing cost, hypothesis H5. The t-values for the two hypotheses are respectively 5.93 and 5.74, and the P-values for both tests are less than 0.05 percent.

CONCLUSION AND MANAGERIAL IMPLICATIONS